Inventorship in AI-Assisted Inventions: Designing an Experiment to Shape Case Law

TL;DR

This paper discusses the challenges of determining inventorship in AI-assisted inventions and proposes an experimental methodology to develop relevant case law involving AI stakeholders.

Contribution

It introduces a novel experimental framework to shape legal standards for AI-assisted inventorship through stakeholder-involved case selection.

Findings

Proposes a methodology for conducting experiments to influence inventorship case law.

Highlights the need for new legal approaches due to AI's role in invention.

Suggests involving AI stakeholders to better understand human contribution in AI-assisted inventions.

Abstract

The latest improvements in artificial intelligence (AI) raise new challenges for intellectual property laws, particularly concerning the inventorship issue in AI-assisted inventions - that is, those in which AI is used in the inventive process. While most jurisdictions allow only a natural person to be considered the inventor, the question of how to deal with AI-assisted inventions remains relevant. Namely, what is the nature and contribution of AI tools in an AI-assisted invention that would prevent a human from being recognized as its inventor? The main challenge in addressing this question is the lack of case law on the issue. It is reasonable to assume that with the development of AI and the growing interest in its use in the inventive process, new cases will naturally arise, which in turn will harmonize and address the inventorship issue in AI-assisted inventions to some extent. However, this process will take significant time and may not keep pace with the rapid development of AI, nor fully address the new problems that arise alongside AI advancements. This research proposes the conditions of an experiment to create relevant case law. This experiment could be initiated by society, involving stakeholders specializing in AI. The article also proposes a methodology for conducting the experiment and selecting cases that best reflect the current state of AI use in the inventive process. Conducting such an approach will help identify the most effective methods for measuring human contribution to AI-assisted inventions when determining inventorship.